Abstract
Social media is now a new means of
engagement and a catalyst for citizen science; still, less attention has
been paid to understanding the influence of online communities on
community-led citizen science projects. This study used the Fife Street
Champions public Facebook group as a case study to explore how online
community-led citizen science projects generate citizen science data to
understand littering challenges in Scotland and to examine the impact of
the group’s activities and the challenges they face. Data
driven-content analysis was used to analyse Facebook user-generated data
of 337 posts with comments and images to identify key themes that
emerge in the data. Results indicate that group members develop their
own data collection tools, share, analyse and present their
litter-picking activities to understand the magnitude of littering and
the impact of their litter-picking activities. However, the findings
highlight inconsistencies in how group members collect and record data
from their litter-picking activities. The group also provides
informational support, environmental awareness and advocacy, and
environmental citizenship. Members also share concerns about
eco-anxiety. Lastly, safety and health concerns, COVID-19, and seagulls
are challenges experienced by online-based litter pickers. The results
contribute to our understanding of the opportunity that social media
platforms can provide to build more robust online community-driven
citizen science projects that can inform further research. Key
stakeholders need to collaborate with such communities to improve on
collecting scientifically meaningful data.
Original language | English |
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Article number | 55 |
Pages (from-to) | 1-15 |
Number of pages | 15 |
Journal | Citizen Science: Theory and Practice |
Volume | 8 |
Issue number | 1 |
DOIs | |
Publication status | Published - 22 Sept 2023 |
Keywords
- Citizen science user-generated data
- Litter picking
- Online citizen science
- Environmental citizenship